Evolution strategies-based optimized graph reinforcement learning for solving dynamic job shop scheduling problem.
Chupeng SuCong ZhangDan XiaBaoan HanChuang WangGang ChenLonghan XiePublished in: Appl. Soft Comput. (2023)
Keyphrases
- job shop scheduling problem
- evolution strategy
- reinforcement learning
- graph model
- job shop scheduling
- genetic algorithm
- evolutionary algorithm
- critical path
- combinatorial optimization
- benchmark problems
- scheduling problem
- tabu search
- differential evolution
- simulated annealing
- random walk
- directed graph
- graph structure
- weighted graph
- combinatorial optimization problems
- memetic algorithm
- bipartite graph
- machine learning
- search algorithm
- multi objective
- dynamic programming
- optimization methods
- feasible solution
- genetic programming